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Shashkova TI, Martynova EU, Ayupova AF, Shumskiy AA, Ogurtsova PA, Kostyunina OV, Khaitovich PE, Mazin PV, Zinovieva NA. Development of a low-density panel for genomic selection of pigs in Russia. Transl Anim Sci 2019; 4:264-274. [PMID: 32704985 PMCID: PMC6994047 DOI: 10.1093/tas/txz182] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 11/27/2019] [Indexed: 02/07/2023] Open
Abstract
Genomic selection is routinely used worldwide in agricultural breeding. However, in Russia, it is still not used to its full potential partially due to high genotyping costs. The use of genotypes imputed from the low-density chips (LD-chip) provides a valuable opportunity for reducing the genotyping costs. Pork production in Russia is based on the conventional 3-tier pyramid involving 3 breeds; therefore, the best option would be the development of a single LD-chip that could be used for all of them. Here, we for the first time have analyzed genomic variability in 3 breeds of Russian pigs, namely, Landrace, Duroc, and Large White and generated the LD-chip that can be used in pig breeding with the negligible loss in genotyping quality. We have demonstrated that out of the 3 methods commonly used for LD-chip construction, the block method shows the best results. The imputation quality depends strongly on the presence of close ancestors in the reference population. We have demonstrated that for the animals with both parents genotyped using high-density panels high-quality genotypes (allelic discordance rate < 0.05) could be obtained using a 300 single nucleotide polymorphism (SNP) chip, while in the absence of genotyped ancestors at least 2,000 SNP markers are required. We have shown that imputation quality varies between chromosomes, and it is lower near the chromosome ends and drops with the increase in minor allele frequency. Imputation quality of the individual SNPs correlated well across breeds. Using the same LD-chip, we were able to obtain comparable imputation quality in all 3 breeds, so it may be suggested that a single chip could be used for all of them. Our findings also suggest that the presence of markers with extremely low imputation quality is likely to be explained by wrong mapping of the markers to the chromosomal positions.
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Affiliation(s)
| | | | - Asiya F Ayupova
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | | | | | - Olga V Kostyunina
- Ernst Federal Science Center for Animal Husbandry, Dubrovitsy, Moscow Oblast, Russia
| | | | - Pavel V Mazin
- Skolkovo Institute of Science and Technology, Moscow, Russia.,Computer Science Department, National Research University Higher School of Economics, Moscow, Russia
| | - Natalia A Zinovieva
- Ernst Federal Science Center for Animal Husbandry, Dubrovitsy, Moscow Oblast, Russia
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Ferreira de Camargo GM. The role of molecular genetics in livestock production. ANIMAL PRODUCTION SCIENCE 2019. [DOI: 10.1071/an18013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Genetic variations that lead to easy-to-identify phenotypic changes have always been of interest to livestock breeders since domestication. Molecular genetics has opened up possibilities for identifying these variations and understanding their biological and population effects. Moreover, molecular genetics is part of the most diverse approaches and applications in animal production nowadays, including paternity testing, selection based on genetic variants, diagnostic of genetic diseases, reproductive biotechniques, fraud identification, differentiation of hybrids, parasite identification, genetic evaluation, diversity studies, and genome editing, among others. Therefore, the objective of this review was to describe the different applications of molecular genetics in livestock production, contextualising them with examples and highlighting the importance of the study of these topics and their applications.
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Boré R, Brito LF, Jafarikia M, Bouquet A, Maignel L, Sullivan B, Schenkel FS. Genomic data reveals large similarities among Canadian and French maternal pig lines. CANADIAN JOURNAL OF ANIMAL SCIENCE 2018. [DOI: 10.1139/cjas-2017-0103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Combining reference populations from different countries and breeds could be an affordable way to enlarge the size of the reference populations for genomic prediction of breeding values. Therefore, the main objectives of this study were to assess the genetic diversity within and between two Canadian and French pig breeds (Landrace and Yorkshire) and the genomic relatedness among populations to evaluate the feasibility of an across-country reference population for pig genomic selection. A total of 14 756 pigs were genotyped on two single nucleotide polymorphism (SNP) chip panels (∼65K SNPs). A principal component analysis clearly discriminated Landrace and Yorkshire breeds, and also, but to a lesser extent, the Canadian and French purebred pigs of each breed. Linkage disequilibrium (LD) between adjacent SNPs was similar within Yorkshire populations. However, levels of LD were slightly different for Landrace populations. The consistency of gametic phase was very high between Yorkshire populations (0.96 at 0.05 Mb) and high for Landrace (0.88 at 0.05 Mb). Based on consistency of gametic phase, Canadian and French pig maternal lines are genetically close to each other. These results are promising, as they indicate that the accuracy of estimated genomic breeding values may increase by combining reference populations from the two countries.
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Affiliation(s)
- Raphael Boré
- Institut de la Filière Porcine, La Motte au Vicomte, BP 35104, Le Rheu, France
| | - Luiz F. Brito
- Centre for Genetic Improvement of Livestock, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, Canada
| | - Mohsen Jafarikia
- Centre for Genetic Improvement of Livestock, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, Canada
- Canadian Centre for Swine Improvement, Central Experimental Farm, Building No. 75, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada
| | - Alban Bouquet
- Institut de la Filière Porcine, La Motte au Vicomte, BP 35104, Le Rheu, France
| | - Laurence Maignel
- Canadian Centre for Swine Improvement, Central Experimental Farm, Building No. 75, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada
| | - Brian Sullivan
- Canadian Centre for Swine Improvement, Central Experimental Farm, Building No. 75, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada
| | - Flávio S. Schenkel
- Centre for Genetic Improvement of Livestock, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, Canada
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Putz AM, Tiezzi F, Maltecca C, Gray KA, Knauer MT. A comparison of accuracy validation methods for genomic and pedigree-based predictions of swine litter size traits using Large White and simulated data. J Anim Breed Genet 2017; 135:5-13. [PMID: 29178316 DOI: 10.1111/jbg.12302] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 10/07/2017] [Indexed: 11/28/2022]
Abstract
The objective of this study was to compare and determine the optimal validation method when comparing accuracy from single-step GBLUP (ssGBLUP) to traditional pedigree-based BLUP. Field data included six litter size traits. Simulated data included ten replicates designed to mimic the field data in order to determine the method that was closest to the true accuracy. Data were split into training and validation sets. The methods used were as follows: (i) theoretical accuracy derived from the prediction error variance (PEV) of the direct inverse (iLHS), (ii) approximated accuracies from the accf90(GS) program in the BLUPF90 family of programs (Approx), (iii) correlation between predictions and the single-step GEBVs from the full data set (GEBVFull ), (iv) correlation between predictions and the corrected phenotypes of females from the full data set (Yc ), (v) correlation from method iv divided by the square root of the heritability (Ych ) and (vi) correlation between sire predictions and the average of their daughters' corrected phenotypes (Ycs ). Accuracies from iLHS increased from 0.27 to 0.37 (37%) in the Large White. Approximation accuracies were very consistent and close in absolute value (0.41 to 0.43). Both iLHS and Approx were much less variable than the corrected phenotype methods (ranging from 0.04 to 0.27). On average, simulated data showed an increase in accuracy from 0.34 to 0.44 (29%) using ssGBLUP. Both iLHS and Ych approximated the increase well, 0.30 to 0.46 and 0.36 to 0.45, respectively. GEBVFull performed poorly in both data sets and is not recommended. Results suggest that for within-breed selection, theoretical accuracy using PEV was consistent and accurate. When direct inversion is infeasible to get the PEV, correlating predictions to the corrected phenotypes divided by the square root of heritability is adequate given a large enough validation data set.
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Affiliation(s)
- A M Putz
- Department of Animal Science, North Carolina State University, Raleigh, NC, USA
| | - F Tiezzi
- Department of Animal Science, North Carolina State University, Raleigh, NC, USA
| | - C Maltecca
- Department of Animal Science, North Carolina State University, Raleigh, NC, USA
| | - K A Gray
- Smithfield Premium Genetics, Rose Hill, NC, USA
| | - M T Knauer
- Department of Animal Science, North Carolina State University, Raleigh, NC, USA
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Samorè AB, Fontanesi L. Genomic selection in pigs: state of the art and perspectives. ITALIAN JOURNAL OF ANIMAL SCIENCE 2016. [DOI: 10.1080/1828051x.2016.1172034] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Lopez BM, Kang HS, Kim TH, Viterbo VS, Kim HS, Na CS, Seo KS. Optimization of Swine Breeding Programs Using Genomic Selection with ZPLAN. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2016; 29:640-5. [PMID: 26954222 PMCID: PMC4852224 DOI: 10.5713/ajas.15.0842] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Revised: 12/03/2015] [Accepted: 01/07/2016] [Indexed: 11/27/2022]
Abstract
The objective of this study was to evaluate the present conventional selection program of a swine nucleus farm and compare it with a new selection strategy employing genomic enhanced breeding value (GEBV) as the selection criteria. The ZPLAN+ software was employed to calculate and compare the genetic gain, total cost, return and profit of each selection strategy. The first strategy reflected the current conventional breeding program, which was a progeny test system (CS). The second strategy was a selection scheme based strictly on genomic information (GS1). The third scenario was the same as GS1, but the selection by GEBV was further supplemented by the performance test (GS2). The last scenario was a mixture of genomic information and progeny tests (GS3). The results showed that the accuracy of the selection index of young boars of GS1 was 26% higher than that of CS. On the other hand, both GS2 and GS3 gave 31% higher accuracy than CS for young boars. The annual monetary genetic gain of GS1, GS2 and GS3 was 10%, 12%, and 11% higher, respectively, than that of CS. As expected, the discounted costs of genomic selection strategies were higher than those of CS. The costs of GS1, GS2 and GS3 were 35%, 73%, and 89% higher than those of CS, respectively, assuming a genotyping cost of $120. As a result, the discounted profit per animal of GS1 and GS2 was 8% and 2% higher, respectively, than that of CS while GS3 was 6% lower. Comparison among genomic breeding scenarios revealed that GS1 was more profitable than GS2 and GS3. The genomic selection schemes, especially GS1 and GS2, were clearly superior to the conventional scheme in terms of monetary genetic gain and profit.
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Affiliation(s)
- B M Lopez
- Department of Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea
| | - H S Kang
- Department of Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea
| | - T H Kim
- Department of Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea
| | - V S Viterbo
- Department of Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea
| | - H S Kim
- Department of Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea
| | - C S Na
- Department of Animal Biotechnology, Chonbuk National University, Jeonbuk 561-756, Korea
| | - K S Seo
- Department of Animal Science and Technology, Sunchon National University, Suncheon 540-742, Korea
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Muir WM, Cheng HW, Croney C. Methods to address poultry robustness and welfare issues through breeding and associated ethical considerations. Front Genet 2014; 5:407. [PMID: 25505483 PMCID: PMC4244538 DOI: 10.3389/fgene.2014.00407] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2014] [Accepted: 11/03/2014] [Indexed: 11/13/2022] Open
Abstract
As consumers and society in general become more aware of ethical and moral dilemmas associated with intensive rearing systems, pressure is put on the animal and poultry industries to adopt alternative forms of housing. This presents challenges especially regarding managing competitive social interactions between animals. However, selective breeding programs are rapidly advancing, enhanced by both genomics and new quantitative genetic theory that offer potential solutions by improving adaptation of the bird to existing and proposed production environments. The outcomes of adaptation could lead to improvement of animal welfare by increasing fitness of the animal for the given environments, which might lead to increased contentment and decreased distress of birds in those systems. Genomic selection, based on dense genetic markers, will allow for more rapid improvement of traits that are expensive or difficult to measure, or have a low heritability, such as pecking, cannibalism, robustness, mortality, leg score, bone strength, disease resistance, and thus has the potential to address many poultry welfare concerns. Recently selection programs to include social effects, known as associative or indirect genetic effects (IGEs), have received much attention. Group, kin, multi-level, and multi-trait selection including IGEs have all been shown to be highly effective in reducing mortality while increasing productivity of poultry layers and reduce or eliminate the need for beak trimming. Multi-level selection was shown to increases robustness as indicated by the greater ability of birds to cope with stressors. Kin selection has been shown to be easy to implement and improve both productivity and animal well-being. Management practices and rearing conditions employed for domestic animal production will continue to change based on ethical and scientific results. However, the animal breeding tools necessary to provide an animal that is best adapted to these changing conditions are readily available and should be used, which will ultimately lead to the best possible outcomes for all impacted.
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Affiliation(s)
- William M. Muir
- Department of Animal Sciences, Purdue UniversityWest Lafayette, IN, USA
| | - Heng-Wei Cheng
- Livestock Behavior Research Unit, United States Department of Agriculture – Agricultural Research ServiceWest Lafayette, IN, USA
| | - Candace Croney
- Department of Comparative Pathobiology and Department of Animal Sciences, Purdue UniversityWest Lafayette, IN, USA
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Henryon M, Berg P, Sørensen A. Animal-breeding schemes using genomic information need breeding plans designed to maximise long-term genetic gains. Livest Sci 2014. [DOI: 10.1016/j.livsci.2014.06.016] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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